Standard clinical assessment of brain tumor response to treatment consists of examining contrast enhancement and T2-weighted signal abnormalities on standard magnetic resonance imaging (MRI) scans. While these techniques provide important information regarding tumor pathophysiology, they do not enable direct visualization of tumor growth and invasion. Numerous studies over the past 20 years have shown that tumor cell invasion extends well beyond the margins of abnormalities detected on traditional MRI scans, and this invasion is the primary reason for poor prognosis and 100% fatality rate in glioblastoma multiforme (GBM), the most common and malignant type of brain tumor. Therefore, the overall goal of this project is to establish a valuable clinical imaging biomarker fr visualization and quantification of brain tumor growth and invasion using diffusion MRI techniques. We have demonstrated in our preliminary data that diffusion MRI is sensitive to tumor cell density, and voxel-wise changes in diffusion MRI over time can be used to predict the response to both chemotherapy and anti-angiogenic therapies. In a recent manuscript, we have developed a novel spatiotemporal model of ADC change aimed at quantifying voxel-wise microscopic proliferation and cell invasion rates termed Cell Invasion, Motility, and Proliferation Level Estimate (CIMPLE) maps. Our preliminary data suggests CIMPLE maps correlate with MR spectroscopy measurements of malignant potential, correlate with tumor grade, may predict regions of future contrast enhancement, predict survival in patients with recurrent glioblastoma treated with bevacizumab, and spatially correlates well with abnormal positron emission tomography measurements of amino acid uptake. Despite promising preliminary results from our laboratory, more testing and improvements are necessary as outlined in the specific experiments in the current proposal. Specific Aim #1 focuses on improving the diffusion-weighted image acquisition for advanced CIMPLE map applications by exploring the use of high angular resolution diffusion imaging (HARDI). Success of this specific aim will allow CIMPLE maps to be calculated with high accuracy through higher signal-to-noise diffusion images as well as create a tensor-based solution to CIMPLE maps that may provide directionally-specific maps of tumor invasion. Specific Aim #2 will focus on testing whether CIMPLE maps calculated during radiotherapy are early predictive biomarkers of tumor response to standard therapy. Specifically, we aim to determine whether CIMPLE maps accurately predict spatial regions of future tumor progression as well as predict six- and twelve-month progression-free and overall survival. Lastly, Specific Aim #3 will focus on validating CIMPLE maps through the use of histological information at tumor recurrence and 18F-fluoro-thymidine positron emission tomography measurements of tumor proliferation. Successful completion of this aim will provide additional evidence validating non-invasive CIMPLE map measurements of proliferation and invasion rate.